code: def test_ordered_encoding_1_variable_ignore_format(df_enc_numeric):
      encoder = OrdinalEncoder(
          encoding_method="ordered",
          variables=["var_A"],
          ignore_format=True,
      )
      encoder.fit(
          df_enc_numeric[["var_A", "var_B"]], df_enc_numeric["target"]
      )
      X = encoder.transform(df_enc_numeric[["var_A", "var_B"]])
  
      # expected output
      transf_df = df_enc_numeric.copy()
      transf_df["var_A"] = [
          1,
          1,
          1,
          1,
          1,
          1,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          2,
          2,
          2,
          2,
      ]
  
      # test init params
      assert encoder.encoding_method == "ordered"
      assert encoder.variables == ["var_A"]
      # test fit attr
      assert encoder.variables_ == ["var_A"]
      assert encoder.encoder_dict_ == {"var_A": {1: 1, 2: 0, 3: 2}}
      assert encoder.n_features_in_ == 2
      # test transform output
      pd.testing.assert_frame_equal(X, transf_df[["var_A", "var_B"]])
  
file_path: feature_engine/tests/test_encoding/test_ordinal_encoder.py
imports: import numpy
  import pandas
  import pytest
  from feature_engine.encoding import OrdinalEncoder
label_desc: Use image node_id 8 for calling a global function with example usage: test_ordered_encoding_1_variable_ignore_format(df_enc_numeric) without return types